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Adding input pertubation #3293
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@isamu-isozaki Do this trick related to noise offset? |
@xiaohu2015 Good question! And very similar implementation but the idea/what they do is very different. Noise offset adds another normal distribution to reduce the low-frequency noise to make stable diffusion able to generate images that it originally can't. Implementation-wise this is
For input perturbation, the idea is to make the model's training robust to an error during inference(some random noise at x_t). To do this we do
so, in input perturbation, the objective is to ignore the new noise added while for offset noise, it's included for more info. Let me know if that makes sense! |
@isamu-isozaki another work is https://arxiv.org/abs/2305.08891 |
@xiaohu2015 ohh I was planning to read that paper. Thanks for the send! |
This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread. Please note that issues that do not follow the contributing guidelines are likely to be ignored. |
Closing since merged |
Input perturbation is a very simple change proposed here where we add noise during training to make the trainer robust to the error accumulation during inference. This got state-of-the-art on the celeb dataset as can be seen here
I made a pr here
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